Inventory Optimization with SAP - cdn.ttgtmedia.com · Contents at a Glance Introduction..... 19 1 Why Inventory Is Necessary..... 27

Marc Hoppe

Inventory Optimization with SAP®

Contents at a Glance

Introduction ....................................................................... 19

1 Why Inventory Is Necessary .............................................. 27

2 Factors Influencing Inventory ............................................ 45

3 Inventory Analysis ............................................................. 53

4 Demand Planning and Forecasting .................................... 93

5 Material Requirements Planning ....................................... 207

6 Service Level and Safety Stocks ......................................... 257

7 Lot Sizes ............................................................................. 325

8 Production ......................................................................... 365

9 Inventory Controlling ......................................................... 437

10 Afterword ........................................................................... 467

A Literature ........................................................................... 473

B The Author ......................................................................... 475

Index .................................................................................. 477

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Contents

Introduction ........................................................................................... 19

1 Why Inventory Is Necessary .............................................. 27

1.1 Different Inventory Concepts ................................................. 281.1.1 Inventories as Enabling Agents .................................. 281.1.2 Inventories as Concealers of Weak Processes ............. 321.1.3 Inventory as an Adjusting Screw ................................ 35

1.2 Uncertainties in the Supply Chain .......................................... 361.2.1 Demand-Side Uncertainties ....................................... 37

Consumption Variances ....................................... 371.2.2 Supply-Side Uncertainties ......................................... 37

Delivery Date Variances ....................................... 37Delivery Quantity Variances ................................. 38Price Variances .................................................... 38Inventory Variances ............................................. 39

1.3 How to Deal With Uncertainties ............................................ 391.3.1 Demand-Side Optimization Potentials ....................... 401.3.2 Supply-Side Optimization Potentials ......................... 411.3.3 Comprehensive Optimization Measures .................... 43

2 Factors Influencing Inventory ............................................ 45

2.1 Five Instruments .................................................................... 452.1.1 Demand Planning ..................................................... 462.1.2 Material Requirements Planning (MRP) ..................... 472.1.3 Service Level and Safety Stocks ................................. 482.1.4 Lot Sizes ................................................................... 502.1.5 Production ................................................................ 50

2.2 Controlling by Inventory Monitoring ...................................... 52

3 Inventory Analysis .............................................................. 53

3.1 Inventory Analysis Options .................................................... 543.1.1 ABC Analysis ............................................................. 543.1.2 XYZ Analysis ............................................................. 60

3.2 ABC Analysis With SAP .......................................................... 613.2.1 Outlining the Analysis Process ................................... 623.2.2 Determining the Analysis Goal .................................. 63

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3.2.3 Defining the Area to be Analyzed .............................. 633.2.4 Calculating the Data Basis ......................................... 663.2.5 Defining the ABC Strategy ......................................... 68

Total Key Figure (%) ............................................ 69Number of Characteristic Values (%) .................... 70Key Figure (absolute) ........................................... 70Number of Characteristic Values .......................... 70

3.2.6 Defining Class Limits ................................................. 713.2.7 Assigning Classes ....................................................... 723.2.8 Evaluating an ABC Analysis ....................................... 73

Totals Curve ......................................................... 733D Graphic .......................................................... 74

3.2.9 Performing an ABC Segmentation ............................. 743.2.10 Case Scenario: ABC Analysis for Warehouse

Optimization ............................................................. 773.2.11 Case Scenario: ABC Quantity Flow Analysis ............... 79

3.3 XYZ Analysis With SAP .......................................................... 813.3.1 Running Analyses in mySAP ERP ............................... 813.3.2 Performing Valuations in Excel .................................. 84

3.4 Combining ABC and XYZ Analyses ......................................... 873.4.1 Optimization Using the ABC-XYZ Matrix ................... 87

Deriving Optimization Potentials ......................... 87An Example from the Trading Industry ................. 89

3.4.2 An ABC-XYZ Matrix With SAP ................................... 90

4 Demand Planning and Forecasting .................................... 93

4.1 The Influence of Demand Planning on Inventories ................. 934.2 The Bullwhip Effect ................................................................ 964.3 Optimization Potentials for the Forecast ................................ 97

4.3.1 Analyzing Market Influences ..................................... 98Market Dynamics ................................................. 98The Marketplace .................................................. 99Competitors ......................................................... 100

4.3.2 Analyzing Product Influences .................................... 100Product Lifecycle ................................................. 100Cannibalization .................................................... 102Lifecycle Planning Using SAP APO ....................... 102Like Modeling ...................................................... 103Phase-in-/Phase-out Modeling ............................. 104

4.3.3 Creating a Consistent Data Basis ............................... 106Historical Consumption (Actual Data) .................. 106

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Data Quality Requirements .................................. 107Correcting the Historical Data Basis ..................... 109Correcting the Work Days .................................... 113Correcting Outliers .............................................. 114Time Series Patterns ............................................. 115

4.3.4 Defining the Optimal Forecast Horizon ..................... 116Flexibility by Short Forecast Horizons ................... 116Defining the Forecast Horizon in SAP APO .......... 117

4.3.5 Considering Promotions ............................................ 118Segmenting Promotions ....................................... 119Forecast Horizon for Promotions .......................... 121Allocations with Scarce Supplies .......................... 121Cannibalization in Promotions ............................. 122Separating the Promotion Data Basis ................... 123The Promotion Planning Process .......................... 124Promotion Planning in SAP APO .......................... 124

4.3.6 Defining Forecast Responsibilities ............................. 127Forecast Levels (Aggregation/Disaggregation) ...... 128Sales Goals and Bonuses Based on Forecast Accuracy .............................................................. 130

4.4 Selecting the Forecast Method .............................................. 1324.4.1 Different Forecast Methods ....................................... 132

Qualitative Forecast Methods .............................. 132Quantitative Forecast Methods ............................ 133Time Series Analysis (Univariate Models) ............. 134Causal Models ..................................................... 135Naive Methods .................................................... 136Composite Forecast Methods ............................... 136

4.4.2 Procedure Model for the Selection ............................ 136Step 1: Data Analysis ........................................... 137Step 2: Selecting the Selection Model .................. 138Drawbacks of Automatic Model Selection ............ 146

4.5 Details of the Individual Forecast Methods ............................ 1484.5.1 Unstable Demand and Incomplete History ................ 148

Manual Forecast .................................................. 148Moving Average Model ....................................... 149Weighted Moving Average Model ....................... 149Composite Forecast Methods ............................... 150Bass Model .......................................................... 151Two-Points Function ............................................ 152

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4.5.2 Stable Demand and Incomplete History .................... 153Constant Model of First-Order Exponential Smoothing ........................................................... 153Trend Models and Seasonal Models of First-Order Exponential Smoothing .............................. 156Models of Second-Order Exponential Smoothing ........................................................... 156The Holt Procedure .............................................. 157The Winters Procedure ........................................ 157

4.5.3 Unstable Demand and Complete History ................... 159Seasonal Linear Regression .................................. 159The Croston Method ............................................ 161Box-Jenkins Method/ARIMA ................................ 162Median Method .................................................. 163

4.5.4 Stable Demand and Complete History ....................... 164Multilinear Regression (Causal Models) ................ 164Lifecycle Forecast ................................................. 167Summary ............................................................. 169

4.6 Running a Forecast ................................................................ 1704.6.1 Configuring the Settings ............................................ 171

Step 1: Optimizing the Parameters ....................... 171Step 2: Composite Forecast .................................. 172Step 3: Forecast Periods ....................................... 173Step 4: Promotions and Events ............................ 174

4.6.2 Running a Forecast in SAP APO ................................ 175The Demand Planning Desktop ............................ 175Running the Forecast ........................................... 178Forecast Analysis .................................................. 180Forecast Comparison ........................................... 184

4.7 Forecast Accuracy and Alert Functions ................................... 1864.7.1 Ex-Post Forecast ........................................................ 1864.7.2 An Overview of Forecast Errors ................................. 1884.7.3 Univariate Forecast Errors ......................................... 189

Error Total ........................................................... 189Mean Absolute Deviation (MAD) ......................... 190Mean Square Error (MSE) ..................................... 190Root of the Mean Square Error (RMSE) ................ 191Absolute Percent Error (APE) ............................... 191Adjusted Absolute Percent Error (APE-A) ............. 193Mean Absolute Percent Error (MAPE) .................. 193

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Median Absolute Percent Error (MdAPE) ............. 194Relative Absolute Error (RAE) .............................. 195Median Relative Absolute Error (MdRAE) ............ 195Geometric Mean Relative Absolute Error (GMRAE) ............................................................. 195Tracking Signal ..................................................... 196Theil Coefficient ................................................... 196Summary of Univariate Errors ............................... 196

4.7.4 Causal Forecast Errors (MLR) ..................................... 197R Square .............................................................. 197Adjusted R Square ............................................... 197Durbin-h .............................................................. 198Durbin-Watson .................................................... 198t-Test ................................................................... 199Mean Elasticity .................................................... 199

4.7.5 Forecast Errors in SAP APO ....................................... 2004.7.6 Comparability of Forecast Errors ................................ 201

Comparable Data Basis ........................................ 201Comparable Forecast Periods ............................... 201Comparable Aggregation Levels ........................... 202Comparable Points in Time .................................. 202

4.7.7 Forecast Accuracy ..................................................... 2034.7.8 Alert Monitor ............................................................ 204

5 Material Requirements Planning ....................................... 207

5.1 MRP Strategies ...................................................................... 2085.1.1 Requirements Calculation ......................................... 2085.1.2 Balance Accumulation ............................................... 2095.1.3 Order Calculation ...................................................... 209

5.2 Impact of Material Requirements Planning on Inventory ........ 2095.3 Strategies for Make-to-Stock Production in mySAP ERP ......... 211

5.3.1 Planning with Final Assembly (40) ............................. 2135.3.2 Production by Lot Size (30) ....................................... 2165.3.3 Net Requirements Planning (10) ............................... 2185.3.4 Gross Requirements Planning (11) ............................. 2205.3.5 Planning Without Final Assembly (52) ....................... 2225.3.6 Planning with Planning Material (63) ........................ 226

5.4 Strategies for Planning Components in mySAP ERP ................ 2295.4.1 Planning at Assembly Level (70) ................................ 2295.4.2 Planning at Phantom Assembly Level (59) ................ 231

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5.5 Strategies for Make-to-Order Production in mySAP ERP ........ 2345.5.1 Planning Without Final Assembly for Make-to-

Order Production (50) ............................................... 2355.5.2 Make-to-Order Production (20) ................................ 237

5.6 Consumption-Based Material Requirements Planning Using mySAP ERP .................................................................. 2395.6.1 Reorder Point Planning ............................................. 2395.6.2 Forecast-Based Material Requirements Planning ....... 2425.6.3 Time-Phased Materials Planning ............................... 2425.6.4 Range of Coverage Profile in Time-Phased

Materials Planning .................................................... 2445.6.5 Time-Phased Materials Planning with Delivery

Cycle ......................................................................... 2465.6.6 Time-Phased Materials Planning with Reorder

Point Planning .......................................................... 2485.7 Requirements Strategies in SAP APO ..................................... 2485.8 Potential for Optimization in Material Requirements

Planning ................................................................................ 2515.8.1 Stockholding on Different BOM Levels ...................... 251

Two Levels Below the Finished Product ............... 251One Level Below the Finished Product ................. 251No Stockholding of Components ......................... 252

5.8.2 Optimize Master Data Parameters ............................. 2525.8.3 Selection of the Correct MRP Strategy ....................... 254

Which Planning Level Should You Use for Your Planning? .................................................... 254Which Production Strategy Should You Use? ....... 255Which Procurement Strategy is Appropriate for Your Products? ............................................... 256Which Department is Responsible? ...................... 256Influence of Inventory on Material Require-ments Planning .................................................... 256

6 Service Level and Safety Stocks ......................................... 257

6.1 Safety Stock ........................................................................... 2576.2 Service Level .......................................................................... 259

6.2.1 Considerations and Goals .......................................... 259Readiness to Deliver ............................................ 260Delivery Reliability ............................................... 263Delivery Time ...................................................... 264

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Delivery Flexibility ............................................... 265Delivery Quality ................................................... 266

6.2.2 Service Level Optimization Potentials ........................ 266Disruptions in Order Processing ........................... 266Disruptions in Planning ........................................ 268Disruptions in Production .................................... 269Disruptions in Master Data .................................. 270Factors That Influence the Service Level ............... 270

6.2.3 Optimization with Order Processing in mySAP ERP ... 2716.2.4 Optimization With Global ATP in SAP APO ............... 272

Global ATP in SAP APO ....................................... 274Basic Methods ..................................................... 274Enhanced Methods .............................................. 275Rule-Based Check ................................................ 276Explanation and Simulation .................................. 276At Various Product Levels .................................... 277At Various Organizational Levels .......................... 278Controlling the Product Selection ........................ 278Processing for Several Plants ................................ 279Multiple Simultaneous Checks ............................. 279In Materials Management .................................... 280

6.3 Replenishment Lead Time ...................................................... 2806.3.1 Replenishment Lead Time in mySAP ERP .................. 2806.3.2 Optimization Potentials Related to RLT ..................... 283

6.4 Forecast Quality .................................................................... 2836.4.1 Normal Distribution .................................................. 2836.4.2 Normal Distribution with Variances .......................... 285

6.5 Safety Stock ........................................................................... 2866.5.1 Standard Safety Stock Planning in mySAP ERP ........... 288

Safety Stocks in mySAP ERP ................................. 289Dynamic Safety Stock ........................................... 291Safety Time .......................................................... 296Safety Stock Available for MRP ............................ 298

6.5.2 Optimization Potentials in Safety Stocks .................... 3016.5.3 Optimization with SAP APO ...................................... 3026.5.4 Standard Safety Stock Planning ................................. 304

Static Methods in SAP APO ................................. 305Dynamic Methods in SAP APO ............................ 308Using Standard Methods in SAP APO .................. 310Advantages and Disadvantages of the Standard Methods ............................................... 310

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6.5.5 Enhanced Safety Stock Planning ................................ 311Determining the Service Level .............................. 313Determining Forecast Quality .............................. 314Calculating the Safety Stock ................................. 316Advantages and Disadvantages of the Enhanced Methods .............................................. 322

7 Lot Sizes ............................................................................. 325

7.1 How Do Lot Sizes Affect Stocks ............................................. 3257.2 Stochastic (Static) Lot-Sizing Procedure in mySAP ERP

and SAP APO ......................................................................... 3277.2.1 Exact Lot Size ............................................................ 3287.2.2 Fixed Lot Size ............................................................ 3297.2.3 Fixed Lot Size with Splitting and Overlapping ............ 3307.2.4 Replenishment up to Maximum Stock Level .............. 3307.2.5 Calculating the Lot Size ............................................. 3317.2.6 Evaluating Stochastic Procedures ............................... 332

7.3 Deterministic (Periodic) Lot-Sizing Procedures in mySAP ERP and SAP APO ...................................................... 3337.3.1 Periodic Lot-Sizing Procedures .................................. 3337.3.2 Fixed Ranges in mySAP ERP ...................................... 336

Statistical Range of Coverage Calculation with Range of Coverage Profile ............................ 337Safety Time/Actual Range of Coverage ................. 340Days’ Supply and Receipt Days’ Supply ................ 340Actual Range of Coverage .................................... 340

7.3.3 Period-Specific Fixed Ranges of Coverage in SAP APO ................................................................... 341

7.3.4 Additional Lot-Sizing Procedures in SAP APO ........... 3427.3.5 Continuous Input and Output ................................... 342

Discrete Input—Continuous Output ..................... 343Continuous Input—Continuous Output ................ 345Continuous Input—Discrete Output ..................... 345

7.3.6 Summary ................................................................... 3467.4 Optimal Lot-Sizing Procedures in mySAP ERP and

SAP APO ............................................................................... 3477.4.1 Taking Costs into Account in Economic Procedures ... 347

Material Costs ...................................................... 348Ordering Costs ..................................................... 348Production Costs ................................................. 348Stockholding Costs .............................................. 349

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Stockout Costs ..................................................... 349Cost Optimization ................................................ 349

7.4.2 Andler Lot Size (Harris Method) ................................ 3507.4.3 Part-Period Balancing (Cost-Balancing Method) ........ 3527.4.4 Least Unit Cost Procedure ......................................... 3547.4.5 Groff Lot-Sizing Procedure ........................................ 3567.4.6 Dynamic Lot-Size Calculation .................................... 3577.4.7 Optimal Lot-Sizing Procedure in SAP APO ................ 3597.4.8 Comparison of Lot-Sizing Procedures in SAP ............. 361

7.5 Restrictions in the Lot-Size Calculation .................................. 3617.6 Selecting Lot-Sizing Procedures ............................................. 363

8 Production .......................................................................... 365

8.1 How Do Backlogs in Production Affect Stocks? ...................... 3658.2 Why Do Backlogs Occur in Production Planning? ................... 370

8.2.1 The Cause: The MRP-II Concept ................................ 3708.2.2 The Evolution: From MRP to APS .............................. 371

The Problem With MRP-II ................................... 371Further Development of the MRP-II Concept ....... 372

8.3 Reduction of Backlogs ........................................................... 3738.3.1 Realistic Production Plans ......................................... 373

Characteristics of a Good Plan .............................. 373Operational Criteria of a Good Plan ..................... 373Goal Conflicts ...................................................... 374

8.3.2 The Finite Production Plan ........................................ 374Characteristics of a Finite Plan ............................. 374Outlets in the Production Plan ............................. 375MRP Heuristics and Finite Planning ..................... 375Resolving Backlogs ............................................... 377

8.4 Finite Planning and Optimization in SAP APO ....................... 3798.4.1 Concurrent, Finite Material and Capacity Planning .... 380

Automatic Planning ............................................. 380Pegging ............................................................... 382

8.4.2 Planning Heuristics (PP/DS Planning Run) ................. 387What Are Heuristics? ........................................... 387Product Heuristics ................................................ 388MRP Heuristics .................................................... 398Service Heuristics ................................................. 400Detailed Scheduling Heuristics ............................. 402Customer-Specific Heuristics ................................ 411

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8.4.3 Optimization Methods and Concepts ........................ 412Optimization Goals .............................................. 412Optimization Algorithms ...................................... 414Optimization in SAP APO PP/DS .......................... 414Using Setup Optimization .................................... 416Machine Failure ................................................... 417Integration of External Optimizers ....................... 418

8.4.4 Alerts and Their Forwarding ...................................... 4198.4.5 Comparing Planning Results ...................................... 4208.4.6 CTP: Capable-to-Promise .......................................... 4258.4.7 Embedding Superordinate and Subordinate

Planning Levels ......................................................... 4278.4.8 Separate Planning Tools in APO PP/DS ..................... 431

9 Inventory Controlling ......................................................... 437

9.1 Why Inventory Monitoring? ................................................... 4379.2 An Introduction to Logistics Controlling ................................ 4389.3 The Information System of the Supply Chain Council ............. 4409.4 Problems with Data Collection ............................................... 4459.5 Important Inventory Key Figures ............................................ 446

9.5.1 Range of Coverage .................................................... 446Range of Coverage/Replenishment Lead Times Matrix ........................................................ 447Range of Coverage/Consumption Quantities Matrix .................................................................. 448

9.5.2 Inventory Turnover ................................................... 4499.5.3 Slow-Moving Items ................................................... 4509.5.4 Inventory Value ........................................................ 4529.5.5 Dead Stock ............................................................... 4529.5.6 Average Inventory Level, Consumption, and

Range of Coverage .................................................... 4549.5.7 Receipt Value of Valuated Inventory ......................... 4559.5.8 Safety Stock Buffer .................................................... 4559.5.9 Safety Stock .............................................................. 4569.5.10 Inventory Level at Receipt ......................................... 4579.5.11 Lot Size ..................................................................... 457

9.6 Tools for Inventory Analysis ................................................... 4589.6.1 LMN Analysis ............................................................ 4589.6.2 Flowcharts in Production .......................................... 4589.6.3 Procurement and Consumption Cycles ...................... 460

9.7 Inventory Monitoring in mySAP ERP ...................................... 462

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10 Afterword ........................................................................... 467

Appendix .................................................................................. 473

A Literature ......................................................................................... 473B The Author ...................................................................................... 475

Index ...................................................................................................... 477

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You can optimally tune your supply chain and save a lot of money by reducing your inventory without compromising the level of your cus-tomer service and the utilization of your internal capacities.

Introduction

An important objective in a company’s supply chain management is toensure an efficient inventory management. If you examine the way in whichcompanies are actually handling inventory management, the methodsemployed appear to be good; however, the way in which all aspects integralto inventory management interact is often far from ideal, that is, there needsto be a better system of internal controls for inventory to be managed effi-ciently. So, you frequently hear statements like the following:

“We define the high quality of our services as being our competitive edge, butour service levels are insufficient despite our high stock levels.”

“Our machine assignments change five times a day, but we have no idea of thenumber of sales orders that we are actually putting on hold because of that.”

These statements describe only some of the many problems inherent in sup-ply chains today. Despite all the uncertainties and the corresponding coun-termeasures taken to address these uncertainties, a company’s top priority isstill to ensure as high a service level as possible to customers. On the otherhand, the overall costs must be kept to a minimum.

An important key to success in supply chain management is the optimizationof inventories, because stock surplus quantities result in an increase in costsand lower profit margins, while inventory bottlenecks cause problems inproduction and poor service levels. Warehouse stocks are subject to differentinfluencing factors. This book describes these factors and what you can do toefficiently counteract them.Inventory Causes Costs

Decisions made regarding inventory management can have a direct influenceon the success of a company. Until a few years ago, it was generally assumedthat a high volume of stocks guaranteed a successful future for the company.Today, increasing costs force companies to reduce their inventories andwarehouse stocks. Therefore, the optimization of a company's inventory

Introduction

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becomes an increasingly important tool for helping companies to save costs.The importance of those inventory costs becomes clearer when you look atthe following financial statements:

Table 1 contains the financial statement of EPCOS AG, a manufacturer of pas-sive construction elements. The inventory, which is summarized as “Netstocks,” represents an amount of 205,123 Euro in 2003. This corresponds to14.35% of the entire amount of the company's assets and is the second big-gest cost item.

In Table 2, the financial statement of Beiersdorf AG, a producer of consumergoods, shows that the stocks assume an even bigger portion of the totalassets (672 m Euro), namely 19.89%.

ASSETS (09/30/2003) in €

Liquid assets 195,797

Receivables from goods and services, net 185,292

Net stocks 205,123

Accruals, deferrals, and other assets 38,884

Deferred income taxes 7,523

Current assets, total 632,619

Fixed assets, net 649,527

Intangible assets, net 39,940

Deferred income taxes 1 83,022

Other long-term assets 23,922

Total assets 1,429,030

Table 1 High Inventory Costs in the Financial Statement of EPCOS AG in 2003

ASSETS (12/31/03) in m €

Intangible assets 97

Fixed assets 912

Financial assets 22

Total assets 1,031

Table 2 Financial Statement of Beiersdorf AG in 2003—672 Million Euro of Inventory Costs Represent 19.89% of the Total Assets

Introduction

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These examples show that a company's inventory represents a considerablepercentage of the total assets and the business volume of a company. Thisinventory-total assets ratio applies to some industries more than to others.For example, in mechanical engineering and plant construction, the longproject runtimes and the increasing value of the products over time have astrong impact on a company's financials. In the chemical industry, the valuesare significantly smaller, which is due to the shorter project runtimes and thecheaper material components used; however, even here, you can save a lotof money by optimizing the inventory.

Inventory Cost Elements and Portions

A prerequisite for a long-term inventory optimization is the availability ofprecise information on the inventory costs in your company, and an efficientprocess design and ownership taken for the individual inventories.

Depending on the industry, the stockholding costs can vary considerably.Table 3 contains some general indicators for the different cost portions ofstockholding costs including their value ranges (Hartmann 1999).

The entire amount of stockholding costs represents approximately 16–26%of the average valuated stock. The interest that accumulates on the workingcapital (fixed capital) is the biggest portion of the entire stockholding costs.

Stocks 672

Receivables from goods and services 688

Other receivables and assets 94

Current-asset securities and liquid funds 842

Current assets 2,296

Deferred taxes 28

Accruals and deferrals 23

Total 3,378

ASSETS (12/31/03) in m €

Table 2 Financial Statement of Beiersdorf AG in 2003—672 Million Euro of Inventory Costs Represent 19.89% of the Total Assets (cont.)

Introduction

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Since the list in Table 3 does not contain the stockout costs, the entireamount will be even higher. You can find more information on this topic inChapter 2, Factors Influencing Inventory.

Calculating a Cost Reduction

The key figure diagram from DuPont illustrates how an inventory reductioninfluences the return on investment (ROI) of a company. DuPont was thefirst company to implement this calculation method to determine the ROI.That was back in 1919. Since then, it has been improved several times, andtoday it is an integral part of the performance measurement system in everycompany.

The performance measurement system displays the relationships betweenthe individual cost elements and the fixed and current assets. The inventoriesare part of the stocks, which, in turn, are part of the current assets.

In other words, if you can reduce the stock levels, you can also reduce thecurrent assets. A decrease in current assets reduces the amount of totalassets. Therefore, if the revenue doesn’t change, the asset turnover willincrease. The product resulting from the operating margin (profit-sales ratio)and Mthe asset turnover is the ROI. Therefore, in the above example, aninventory reduction of 10% results in an increase of the ROI by 3.6% foryour company (see Figure 1, bottom line).

Cost Elements Cost Portions in % (in relation to the average valuated stock)

Working capital interest 8–10

Loss, breakage 2–5

Inventory management 1–2

Depreciation 1, 5–2

Plant maintenance 1–2

Disposal 1–2

Taxes 1–2

Insurance 0, 5–1

Total stockholding costs 16–26

Table 3 Stockholding Costs and Their Cost Portions (Source: Hartmann)

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The entire capital of a company consists of the shareholders’ equity and theoutside capital. While the shareholders’ equity is already a part of the com-pany’s property, the outside capital must, for example, be borrowed from abank. The total ROI consists of the return on equity and the return on invest-ment. It is the goal of every company to maximize its profits. One importantaspect here is to invest as little equity and outside capital as possible. There-fore, an inventory reduction will reduce the amount of equity and outsidecapital you have to invest. Consequently, the return on equity or investmentincreases, because the return on equity (return on investment) is the ratiobetween the operating profit and the equity (outside capital). In summary,we can make the following statements: Inventories are a major cost factor inthe company. An inventory optimization can essentially help to reduce costs,which results in a considerable improvement of the company's performanceindicators.

Inventory Management Using mySAP

Two SAP solutions that enable you to control your inventory managementand optimize your inventory are mySAP Enterprise Resource Planning(mySAP ERP) and mySAP Supply Chain Management (mySAP SCM). mySAPERP is the successor to the R/3 system and it controls all business-relevantaccounting, HR, and logistics processes as a backbone system. mySAP SCM isa complementary solution that enables you to equip your company to meetthe challenges of the supply chain management area.

Figure 1 Example of an Inventory Reduction of 10% According to the Performance Measure-ment System Implemented by DuPont

84 84

228 228

8 8 12 12

240 240 5.00% 5.00%137 137 Return on Equity

240 240 8.00 8.29

53 47111 106 1.6 1.658031

150 144.7559 59

39 39

Total Cost

Revenue

Current Assets

Production Material

Material Overhead Costs

Other Costs

Stocks

Earnings bef. Taxes

Revenue

Total AssetsOther Current Assets

Operating Margin

Asset Turnover

Return on Investment

Fixed Assets

Cost ElementProduction Material 0%Material Overhead Costs 0%Other Costs 0%Stocks 10%Other Current Assets 0%

ROI 3.63% Increase

Reduction in %

Introduction

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In this book, you’ll learn how to optimize mySAP ERP by modifying existingsettings and leveraging the interaction between your specific processes andthe SAP system. And you will learn how to do this without incurring anyadditional costs or investments.

You’ll learn how to optimize mySAP SCM by leveraging the inventory man-agement potentials that you can utilize using the SAP APO component.

Structure of this Book

Chapter 1 explains why inventories are necessary in a company, and itdescribes the different inventory concepts that are currently being used. Theend of the chapter describes actual measures that you can implement tocounteract uncertainties in the supply chain.

Chapter 2 describes the effect that individual areas—such as lot sizes, pro-duction planning, and demand planning—have on the inventory, and pro-vides some optimization potentials. These potentials are described in furtherdetail in the subsequent chapters, which mainly illustrate ways for you tooptimize your inventories using mySAP ERP and mySAP SCM.

Chapter 3 focuses on the options available for analyzing inventories anddescribes the measures that you should undertake based on the analysisresults.

Chapter 4 describes the inventory optimization options involved in demandplanning processes. It explains how you can improve the exactness of yourforecasts in your demand planning process.

Chapter 5 focuses on the material requirements planning strategies and theirimpact on the inventory, and it describes how you can optimize the materialrequirements planning (MRP) processes.

Chapter 6 focuses on how inventories impact the service level and securitypolicy. Based on some real-life examples, this chapter explains how you canreduce safety stocks without compromising the service level.

Chapter 7 describes and evaluates the different lot-sizing procedures. Inaddition, it shows you the options available when working with lot sizes,and tells you what you should consider when selecting lot sizes to reduceinventories.

Chapter 8 describes the difference between the MRP planning logic and thesimulation of a material and capacity requirements planning. It also defines

Introduction

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the requirements of a good and feasible production plan, after which itdescribes the potentials that you can implement by using SAP AdvancedPlanner and Optimizer (SAP APO) for the production planning.

Chapter 9 describes the options available for implementing a practical inven-tory and logistics controlling process. In this chapter, you’ll find concretekey figures and analysis options for your inventory management usingmySAP ERP and mySAP SCM.

Chapter 10 describes a tried-and-tested inventory optimization process. Itprovides useful advice on what you can do to optimize the inventories andinventory management processes in your own company. The described pro-cess is designed in such a way that you can implement the inventory optimi-zation by merely optimizing your processes, or by optimizing the mySAPERP and mySAP SCM solutions.

Hamburg, Germany, May 2006Marc Hoppe

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There's no doubt about it—inventory is important. But too much of it is counterproductive. Yet, what is the best way to manage invento-ries? This chapter provides a brief overview of the five instruments that you can use to manage and optimize your inventory—demand planning, material requirements planning (MRP), service level and safety stocks, lot sizes, and production.

2 Factors Influencing Inventory

Today’s supply chain networks can cross both organizational and geographi-cal boundaries. This forces companies to control what cannot be controlled.The future of Supply Chain Management (SCM) depends primarily on theability to quickly react to supply and demand changes and important eventsin the supply chain on a global basis. The faster a supply chain network canadapt to such events, the higher the added value and the more likely it is toinfluence the inventory. Inventory optimization is the key to keeping theprofitability of a company at a constant level and to increasing the com-pany’s competitiveness.

2.1 Five Instruments

Supply chain planning is influenced by a number of factors that cannot beforecast with absolute certainty. For example, when forecasting customerrequirements, there is generally an uncertainty regarding the quantity andthe exact selling date. In addition, disturbances and fluctuations in produc-tion cause deviations in the planned replenishment lead time. For this rea-son, safety stocks are used to secure the supply chain against uncertain influ-ences and the optimization potentials described in Chapter 1, Why Inventoryis Necessary.

Colgate Palmolive was able to increase its forecast accuracy up to 98%, toreduce its inventory by 13%, and to improve its cash flow by 13% by usingmySAP Supply Chain Management (mySAP SCM). Similarly, a manufacturerof handheld computers, who had implemented a new SCM solution, man-

Factors Influencing Inventory2

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aged to reduce the planning cycles by 50%, to increase the inventory turn-over from six to ten times, and to reduce the delivery stocks by 32%. In thatcase, however, an entire range of processes had to be improved, namely thedemand and requirements forecasts, inventory management, productionplanning, and order processing. All these changes were based on the goal ofincreasing the company's competitiveness and on shortening the deliverytimes. In the highly competitive handheld market, factors such as price,availability, and on-time delivery have a direct influence on a company’sgrowth and profitability.

A research carried out by Gartner Group recently predicted that 90% oftoday's leading enterprises that have no SCM strategy will lose their pre-ferred vendor status in the future.

In the following sections, we'll take a closer look at the instruments thatenable us to optimize our inventories.

2.1.1 Demand Planning

The first instrument we’ll consider is demand planning. Demand planningand forecasting are inevitable elements in logistics and the comprehensiveplanning process for the entire company. They are used to create rough real-istic and consistent production plans based on the potential sales volume andthe available budget. A good demand planning leads to a reliable character-istics-based forecasting, which, in turn, is the basis for all subsequent pro-cesses. The results derived from demand planning determine the productionand financial resources. The annual plan and the regular revision of the tar-get plans largely depend on the level of accuracy of sales forecasts and on anefficient production planning.

When planning future sales and production, the planner should not only relyon forecasts. Instead, she must include her knowledge of future markettrends, planned advertising campaigns, and changes to specific productgroups in the planning.

If the forecast sales volumes are smaller than the customer demand, the pre-viously produced stocks will be completely reduced; furthermore, there willbe a need to resort to the safety stock. If the delta between the forecast ofsales and the actual customer demand is too big, it can cause stockouts. Cus-tomers are lost if they turn permanently to the competition. In addition to aloss of sales, a loss of image for the company and market shares can alsoresult.

Five Instruments 2.1

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If demand planning is higher than the actual customer demand, surplusinventories can result, which may have to be scrapped or written off. Thisleads to a lower profit margin and a reduced profitability.

Ultimately, it is the accuracy of the forecast that determines the volume of thesafety stock. If the forecast deviates substantially from the actual demand val-ues, the safety stock is correspondingly high or low respectively. Finally, theplanner determines the primary requirements on the basis of the productionquantities and forwards the data to material requirements planning. Chapter4, Demand Planning and Forecasting, provides further detailed informationon using demand planning as an instrument for optimizing the inventory.

2.1.2 Material Requirements Planning (MRP)

The second instrument, material requirements planning (MRP), is used tocreate and manage the production programs for finished as well as unfin-ished products. For this purpose, customer orders and forecasts are needed.Moreover, all other components of the entire product structure areplanned—down to the lowest level. This is done on the basis of the second-ary requirements, which must be identified by MRP.

Frequently, specific finished products, sub-assemblies, or raw materials mustbe produced or procured in advance to ensure short delivery times whencustomer sales orders come in. This advance planning, which at first is notbased on any sales order, is based on the planned independent requirementsthat are offset against incoming customer sales orders at a later stage. Thistype of planning triggers the procurement of raw materials and the produc-tion of sub-assemblies or final products that will be stored in the warehouse.

MRP monitors inventories and determines the material that will be neededat a specific quantity on a certain date. In addition, MRP automatically gen-erates the procurement proposals necessary for this process. In MRP, a netrequirements calculation is automatically carried out in which the availablewarehouse stock or the planned stock receipts from purchasing or produc-tion are compared with the primary requirements. For a material shortage—if the available inventory is smaller than the required quantity—the systemautomatically generates a procurement proposal. Then, MRP initiates make-or-buy decisions. If dates or quantities change, the planned orders must beautomatically adjusted in the MRP process. MRP must be able to quicklyadjust procurement and production to meet new requirement situations.Choosing the right lot sizes is another task handled by MRP.


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MRP is the interface between demand planning in sales and distribution andproduction planning in production. If demand planning is too high, MRP hasto compensate for the discrepancy by selecting the best safety stock level, thecorrect range calculations, the best delivery rhythm, and optimal lot sizes sothat the optimal quantity can be produced at minimum production costs.

This means that MRP is an important adjustment screw for optimizing inven-tory, because it must find the optimum between the different inventorygoals of sales and distribution (high service level = high inventories) and pro-duction (short lead times = low inventories).

MRP’s influence on the operational result of a company can be expressed asa direct, an indirect, and a non-quantifiable success potential:

The directly quantifiable potential results from the portion of material costs insales or in the prime costs. This cost pool can be influenced by choosing theoptimal lot size, or the level of the optimal safety stock.

An indirectly quantifiable potential represents, for example, the creation ofsupplier relationships, the reduction of overall procurement costs, or theinclusion of inventories in the financial report.

The non-quantifiable success potential becomes manifest in the way the com-pany is viewed by its customers on the basis of a high ability to deliver anddelivery reliability.

Chapter 5, Material Requirements Planning, provides further details on theMRP strategies and parameters you can use to optimize your inventory.

2.1.3 Service Level and Safety Stocks

The decision of a company to provide a comprehensive service level is a stra-tegic one. It must be geared towards other objectives such as cost minimiza-tion and capacity utilization. This means that compromises must be foundand priorities set. To achieve a high service level, you may have to increaseyour warehouse stocks so that you can satisfy the demand with finishedproducts from your stocks. Moreover, production must be able to start pro-cessing an order when it is first released, while distribution must be able todeliver on time. However, keeping warehouse stocks generates stockholdingcosts and therefore counteracts the objective of minimizing cost.

The decision to provide a high service level always requires a definition ofsubgoals that the company wants to pursue. Reliability can be ensured bycreating intermediate storage facilities and final product storage facilities. In


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addition, buffers that you include in production planning ensure that thecapacities can produce the right product at the right time in accordance withthe planning. This, however, causes longer wait times and larger storagequantities, which is why you must use the service level value that causes cus-tomers to accept higher prices and long-term commitments against the actualcosts. Unfortunately, not many companies do that.

If, on the other hand, the company pursues its goal of providing a high deliv-ery flexibility and speed, it must organize its business processes in such away that the planning lead times are as short as possible, especially regardingorder acceptance, planning, and production. In that case, the machine utili-zation buffers are kept small in to shorten the order-processing timeframeand to guarantee a fast delivery and shorter turnaround times for the cus-tomer. Here, the cost risk is rooted in the downtime costs which, for exam-ple, occur when required materials are not delivered on time. Moreover, thecompany must bear additional costs that can hardly be measured whenmachine failures or disruptions result in delayed productions and deliveriesso that confirmed delivery dates cannot be adhered to.

The costs generated by an increase of the service level must be considered onthe basis of profitability aspects. When comparing the costs with the reve-nues, which have been generated by the service level, the services must faroutweigh the costs; otherwise, the business objective of profit maximizationand the long-term existence of the company would be at risk. Contrary to theobjective of cost optimization, however, the service level orientation enablesthe company to better respond to market requirements, which, after all, isthe basis for a complete success. Depending on the focus of a company, thedirection towards a service level increase requires a different orientation andprocessing of the business processes. In this context, striving for speed andflexibility is as important as concentrating on the readiness to deliver, as wellas the delivery time and reliability.

An organization can achieve a readiness to deliver of 99% within a maximumof 48 hours only if it permanently maps peak demands in its inventories;however, since those peaks often occur only sporadically, high inventoriesmust be maintained throughout the entire year. Consequently, the companyfaces increased direct and indirect costs such as high depreciations and accu-mulated depreciations for short product lifecycles.

So, what is the optimal service level that satisfies your customers and com-pensates for the costs? How can the service level be measured and which


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processes support an optimal service level? These and other questions areaddressed in great detail in Chapter 6, Service Level and Safety Stocks.

2.1.4 Lot Sizes

One of the primary goals of MRP is the economic supply of external custom-ers and internal customers, that is, production. Here, MRP must optimize thematerial, order processing, and stockholding costs. Material costs depend onthe order quantities and can be determined on the basis of the net landedcosts. The order-processing costs depend on the specific operations. Theycan be described as proportional staff and material costs for procurement,receiving inspection, invoice verification, and data processing. Stockholdingcosts depend on stockkeeping and can be determined on the basis of thedelivered price, the interest rate for stockkeeping, and the inventory costrate. As a result of the order calculation, you obtain the optimal or cost-effec-tive lot size as a production requirement, which represents the initial valuefor purchasing and production.

For example, if you want to increase your delivery flexibility, you must pro-duce smaller lots, which, in turn, entails a reduced capacity utilization due tolonger machine downtimes that are caused by a higher number of set-upprocesses. At the same time, the set-up and unit costs go up, as well as theprocurement costs in purchasing. Moreover, smaller lots reduce the costsand procurement costs in purchasing. They also reduce the procurementquantities, which results in smaller discounts and rebates; whereas the costpool for the procurement process remains unchanged and acts as a costdriver due to the shorter replenishment cycles.

Chapter 7, Lot Sizes, describes how you can influence your inventories byselecting the right lot-sizing procedures.

2.1.5 Production

The logistics of production is a central functional area within the entire sup-ply chain. The largest portion of the entire added value of a manufacturingcompany is generated within production logistics. All upstream processes,such as procurement, but also all the downstream processes, like distribu-tion, are linked to production. Products are produced and refined withinproduction. The value creation within production logistics is what makesmoney. The essential goals of production are therefore short product leadtimes, low inventories, on-time deliveries, and a high degree of machine uti-lization and customer satisfaction.


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Success factors that lead to a high degree of customer satisfaction and there-fore a long-term relationship with a customer are therefore short deliverytimes and a high delivery reliability. Short delivery times can be achieved byshort product lead times, high delivery reliability, low scrap rates, and a highdegree of capacity utilization. But, short product lead times and a highdegree of capacity utilization are contradictory objectives. The optimizationof these goals is the focus of production planning and control. Productionplanning consists of all the essential planning tasks, such as the creation ofmaster data, work scheduling, and the creation of a production program, aswell as capacity leveling. Basically, production planning comprises all workthat occurs prior to the actual production start. The production programdetermines the type and quantity of items to be produced. This applies tofinal products, semifinished products and subassemblies. The program isalso used to define the most favorable production lots and procurementquantities. The production dates (planned dates) and the order sequence aredefined in capacity scheduling.

Production control monitors and controls the actual production process. Thetask of production control is to ensure the supply of production with mate-rial components and raw materials, as well as the adherence to productiondates. Changes at short notice also entail changes to the short-term produc-tion program. The changes to the production program lead to changes on thesupply side: Orders must be canceled. Suppliers are asked to deliver later orearlier. Suddenly the lot sizes in procurement are no longer optimal. Rushdeliveries must be triggered if a production standstill is imminent, becauseof an insufficient material supply. Not only does this increase the procure-ment costs, but the costs in production also increase as inefficient machinesetup changes become necessary.

Inventory is supposed to avoid such firefighting and to balance those short-term changes. This means that the inventory level must be appropriate sothat, on the one hand, stock surpluses are avoided, and on the other hand,process disturbances can be compensated.

To identify optimization potentials in production, the entire production pro-cess must be considered as a whole, both from the standpoint of productionand costs. The following section summarizes the potential areas for optimi-zation in production:

� Shortening of product lead timesThis leads to an increase in machine capacity, a reduction of inventories,shorter delivery times, and a higher customer satisfaction. Liquidity


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increases due to the shorter delivery times because customers pay earlier.Because individual orders no longer occupy machines as long as they usedto due to the shorter product lead times, a higher number of orders can beprocessed in production. This leads to increased revenues in a demand-driven market.

� Improving unit costsA reduction of the unit costs can be achieved by a high degree of machinecapacity utilization. A set-up optimization and a finite planning lead to areduction of set-up costs and an optimization of the production lots. Thisincreases the capacity utilization. In general, it also increases the variableunit costs; however, it also increases the marginal revenues as the fixedcosts remain unchanged.

Chapter 8 describes the influences of Production on the inventory in greaterdetail and introduces options for using SAP in this context.

2.2 Controlling by Inventory Monitoring

Because the supply chain is very complex, all aspects of the supply chain thatwe have described so far only become clear by using the right controllinginstruments. But many companies will find the “standard key figures” inap-propriate. These figures often cannot be used for the organization or theobjectives pursued in SCM, or they are simply not the right means of control.

One of the most common serious mistakes is the isolated use of logistics keyfigures. For example, if a company measures the professionalism of inven-tory management based only on the inventory turnover or range, the result-ing picture will be blurred. Transport costs must also be considered; other-wise, management will see only the low inventories without noticing thatthe transport costs have risen and this negative effect will outweigh the ben-efits of the positive inventory effects.

You can only take the right action if various key figures are combined intel-ligently into key figure systems. Therefore, the key figures must be consis-tently defined and implemented across the entire company. Today, anappropriate key figure system enables a company to proactively identify andcounteract problems. The description of a holistic key figure system wouldexceed the scope of this book; however, Chapter 9, Inventory Controlling,describes the most important key figures and their relevance to real-life pro-duction processes.

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Before you can optimize your inventories, you must accurately ana-lyze them. This chapter describes how you can implement proven methods to segment your inventories so you can analyze their most important aspects.

3 Inventory Analysis

In the previous chapter, the instruments and potentials available to optimizeand reduce inventory were described. Keeping this in mind, you shouldensure that you take specific actions to optimize your inventory and that youimplement these actions consistently. But, to determine which actions arethe right ones for your company, you must first carry out a detailed analysisof your inventories. You can then use the results of the analysis as a basis fordefining the appropriate inventory optimization measures. From hereon, atheme that runs throughout this book will be the basic analysis principlesdescribed in this chapter.

Note that you should try to avoid making the following mistake, which isunfortunately all too frequently made in many companies: Pressure exertedby top management to reduce the inventory can generally only lead to ashort-term success. For medium-term success, the inventories usually returnto the previous level that existed before the decreed inventory reduction. Toensure medium and long-term success, you should continuously use theseanalysis tools, and you should also use them as a basis for controlling yoursupply-chain processes.

The ABC analysis can be used as an inventory analysis instrument. It is a dataclassification tool. For inventory analyses, these classifications can representmaterial consumptions, goods movements, and material stocks. The materi-als are roughly divided into three classes (A, B, and C).

Then a detailed analysis can be carried out using an XYZ analysis. The XYZanalysis is a classic secondary analysis that is based on the ABC analysis. TheXYZ analysis is used to analyze the weighting of individual units according totheir consumption pattern. This means that a consumption fluctuation keyfigure is determined for each unit. Depending on how regularly a unit is con-sumed, it is assigned to one of the three classes, X, Y, or Z.

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The combination of ABC and XYZ analyses represents the ABC-XYZ matrix. Inthat matrix, you can combine the results of the two analyses and therebyobtain important information on your materials and inventories that enablesyou to define appropriate measures for optimizing your inventory.

This chapter will describe the basic instruments of the ABC and XYZ analysesin more detail. Chapter 9, Inventory Controlling, provides a more detaileddescription of the available inventory analysis options.

3.1 Inventory Analysis Options

3.1.1 ABC Analysis

The ABC analysis is an organizational procedure that can be used to classifylarge data quantities. The data can represent material or processes. It isroughly divided into three classes (A, B, and C).

Pros and Cons of the ABC Analysis

The advantages of the ABC analysis are as follows:

� Ease of useThe ABC analysis can be easily used. Usually, the data already exists, andmost IT systems provide standard ABC analyses. The separation into threeclasses can be carried out using the simplest calculating procedures.

� Use of methods does not depend on analyzed objectsYou can use the ABC analysis not only for analyzing materials, but also forcustomer and vendor data. Moreover, you can examine individual processsteps and cash flows using the ABC analysis.

� Clear graphical presentation of the resultsThe graphical presentation of the ABC analysis enables you to obtain aquick and clear overview of the analyzed data. You will be able to identifytrends faster using a graphical presentation than you could using a tabulardisplay.

There are also some disadvantages about the ABC analysis, which youshouldn’t neglect when using it for inventory analysis purposes:

� Very rough classificationThe separation into three classes (A, B, C) is very rough. Therefore, youshould go into further detail after the first rough analysis and perhapsextend the separation to four or more classes. This may not always be nec-

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essary. But it is advisable for a further subdivision of the C class (the Zclass in the XYZ analysis), because that class typically contains particularlylarge data quantities.

� Provision of consistent dataOne of the pitfalls in the ABC analysis is the provision of consistent data.This data is essential to determine the significance of an ABC analysis. Ifyour data is consistent, the ABC analysis can help you obtain a lot of infor-mation on your product and customer structures; however, if the data isnot consistent, the ABC analysis can be very confusing. You should there-fore pay specific attention to the quality of your data. Note that even SAPdoes not provide some important consistency checks, which means thatyou have to check the consistency of your data by yourself.

Classification Into A, B, and C

The classification into the A, B, and C classes and their typical value and quan-tity percentages can be illustrated using the Lorenz curve (see Figure 3.1).

The quantity portions of materials in Class A are usually approximately 10%,while the value portion represents approximately 70%. This means thatthose materials are the most important ones and have the biggest potentialfor optimization. The quantity portion of materials in Class B is 25%,whereas Class C contains 65% of the materials. Thus, C materials occur mostoften. However, the value of 15% only is the smallest one. They mainlyinvolve automatic processes in order to keep the costs as low as possible.

A general problem that occurs when performing the ABC and XYZ analyses isthe definition of the borders between the individual classes. Basically, nei-ther the number of classes (A, B, C) nor the class boundaries (A = 10%, B =20%, C = 70%) are fixed values. The definition of class boundaries for spe-

Figure 3.1 Classification into A, B, and C Classes Based on the Lorenz Curve

A B C

Value Percentage[ % ]

Quantity Percentage[ % ]10 35 100

70

85100

Lorenz Curve

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cific critical value portions is therefore a subjective decision and can varydepending on the purpose of use. Although SAP does suggest some standardboundaries, you can also use your individual ones (see Figure 3.6 on page61).

For example, in the retail and wholesale trading industries, the Lorenz curveis relatively flat, whereas for technical products, for instance in the manufac-turing industry, it is rather steep.

The stronger the upward bend of the Lorenz curve, the more useful it is totreat its individual parts separately. Still, the separation into three classes hasbecome widely accepted both in theory and daily work.

The ABC analysis is supposed to enable you to focus on the essential pro-cesses in the supply chain. Its goal is to separate the essential from the non-essential.

The focus of the activities is to be directed to the most profitable area (Aparts), while the costs in the other areas are to be reduced by the simplifica-tion of processes (for example, by implementing a usage control).

Although the ABC analysis has been known for a long time and can be easilyused, it is still being ignored in many business areas. But the ABC analysis isa universally usable method of classifying objects. Table 3.1 lists some of thepossible objects.

Object Analysis Goal Classification Criteria

Customer Analysis of the customer sales distri-bution

Customer sales in relation to the overall sales within a period

Customer Analysis of distribution costs per USD of customer sales

Distribution costs per customer in relation to customer sales

Vendor Analysis of monetary procurement volumes per vendor

Vendor procurement volume in relation to the entire procurement volume within a period

Finished products

Analysis of capital tie-up caused by inventories in relation to the annual revenue

Average value of inventory in rela-tion to the annual revenue per item

Semifinished products

Analysis of the distribution of the usage value per period per semifin-ished product

Usage value per period of the semifinished product in relation to all usage values per period

Table 3.1 Possible Objects for an ABC Analysis


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The selection of the appropriate classification criterion is a significant factorfor the ABC analysis. If you choose the right classification criterion for yourproblem, the analysis result enables you to make the right decisions. If youchoose the wrong criterion, the result won’t be satisfactory.

The ABC analysis is used predominantly in materials management and in thesales and distribution department of a company. Here it is used to classifymaterial types and products to be procured and used, as well as to classifyand prioritize customers.

Typically, a small number of materials tends to represent a large portion ofthe overall value; however, you should note that the actual relationshipsbetween quantities and values can differ, depending on the actual organiza-tion.

The following typical classification has been generally established:

� A materialsMaterials of the most valuable class represent 5–10% of the total numberand account for approximately 70–80% of the entire usage value perperiod. These are high-quality materials, which have a high value, andtherefore must be handled with more care by planners than other lowerquality materials.

The prioritized handling of A materials is often reflected in the use ofexact, program-driven requirements planning procedures, an exact inven-tory maintenance and control, an intensive market observation, and theclosing of master contracts with particularly efficient vendors. The coststructures must be controlled precisely and the determination of procure-ment proposals should be carried out based on well defined lot-sizing pro-cesses.

Due to the high value of A materials, it is critical that you are always auto-matically informed in realtime about exceptional situations in the processand that you are optimally supported in the search for a solution. Thelogistics information system in mySAP ERP contains a static monitoringsystem. In SAP APO, the Alert Monitor (see Figure 3.2) alerts you as soonas an exception message occurs.

� B materialsClass B contains all types of materials that represent 15–20% of the totalnumber and 15–20% of the entire usage value per period. For these aver-age materials it makes sense to implement a differentiated procedure. Thismeans that you must decide separately on the planning and analysis meth-

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ods that you want to use for each material group and even for each indi-vidual material within the B class. For this reason, it can be useful to fur-ther subdivide the class of B materials into B1 and B2 materials.

� C materialsC materials contain material types that represent 70–80% of the totalnumber and the remaining 5–10% of the entire usage value per period. Cmaterials are therefore of a low value, and their handling is intended tosimplify work processes and reduce costs.

C materials eat up your yield return. The process costs are disproportion-ally high. They tie up capacities and cause approximately 60% of all pro-curement processes. Here, you should consider other strategies like singlesourcing or even outsourcing.

C materials should be driven in an automated way through the supplychain without any manual effort, because the small value portion shouldnot be inflated by additional manual activities. C materials can generallybe planned using fixed or periodic lot sizes. You should avoid doing a

Figure 3.2 Alert Monitor in SAP APO


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time-consuming inventory analysis if at all possible. However, C materialscan have a substantial influence on the production costs, for example, if aC part is missing, which would obstruct the downstream production pro-cess. This can lead to production downtimes or delays for the B and Amaterials.

For C materials it can also make sense to further subdivide the items intoC1 and C2 materials.

Table 3.2 provides an overview of the different way in which A and C mate-rials are managed.

The costs involved in a professional procurement market research are worth-while only for high-quality A materials. For C materials, it is preferable toimplement automated and lean procurement processes, such as E-procure-ment.

An exact value analysis is mandatory for A materials due to their high valueportion, whereas such an analysis is not necessary for C materials.

For A materials, material requirements planning (MRP) should be determinis-tic while you can use stochastic methods for C materials.

Usually, inventory taking is carried out permanently for A materials. For Cmaterials, the annual inventory taking at the end of a fiscal year is sufficient.

Safety stocks should be as small as possible for A materials, since those mate-rials have a high value, which means that even small stocks would generatea high inventory value. For C parts also, the safety stocks shouldn’t be toohigh, but they can contain more buffers than the A material stocks becausethe value of C materials is lower.

A material C material

Procurement market research Global sourcing E-procurement

Value analysis Mandatory Not necessary

Requirements planning Deterministic Stochastic

Inventory-taking Permanently Once a year

Safety stock Small Large

Order cycle High—JiT Larger cycles

Table 3.2 A and C Materials Require Different Strategies

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A materials should be regularly procured in short order cycles. C materials canbe procured weekly or monthly in fixed lot sizes.

3.1.2 XYZ Analysis

The ABC analysis is a primary analysis. It can be used as a basis for follow-upor secondary analyses such as the segmentation or the XYZ analysis. The XYZanalysis enables you to perform the next step of the inventory analysis. Thefollowing typical classification has been generally established:

� X materialsX materials are characterized by a constant, non-changing usage over time.The requirements fluctuate only slightly around a constant level so thatthe future demand can basically be forecast quite well. Unfortunately,experience has shown that even the forecast for X products can be poor.With X products, it’s important to recognize fluctuations straightaway soyou can respond quickly and appropriately. For this reason, you shouldinstall an outlier correction process, for example, in demand planning (seeFigure 3.3, top).

� Y materialsThe usage of these materials is neither constant nor sporadic. With Ymaterials, you can often observe trends, for example, that the usageincreases or decreases for awhile, or that it is characterized by seasonalfluctuations. For these materials, it’s harder to obtain an accurate forecast(see Figure 3.3, center).

� Z materialsThese materials are not used regularly. The usage can strongly fluctuate oroccur sporadically. In these cases, you can often observe periods with noconsumption at all. The creation of a forecast is extremely demanding andvery difficult. It is useful to further subdivide the Z materials into Z1 andZ2 materials, the latter being used even less regularly than the Z1 materi-als. This enables you to trigger detailed counteractive measures for partic-ularly critical materials (see Figure 3.3, bottom).

The quality of the access fluctuations can also be determined using a fluctua-tion coefficient. This coefficient represents the deviation of the access pat-tern in the current period from that in the previous period. If the fluctuationcoefficient increases, the forecast accuracy decreases. X materials have a fluc-tuation coefficient of < 0.1; Y materials are located between 0.1 and 0.25;and Z materials are > 0.25 (see also Figure 3.4).

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3.2 ABC Analysis With SAP

In the SAP environment, you can use the ABC analysis in different depart-ments of your company.

Figure 3.3 XYZ Analysis with Access and Usage Fluctuations for Materials (Source: FIR)

Figure 3.4 Fluctuation Coefficient in Relation to the Material Portion in an XYZ Analysis

Accesses

Accesses

Accesses

XYZ Analysis: Access and Usage Fluctuations

X

Y

Z

Regular Accesses

SporadicAccesses

Irregular Accesses

0.1 %

100 %

Material Portion

0.25 %

X

Y

Z

Fluc

tuat

ion

Coe

ffici

ent

20 % 80 %

Z Items:- very irregular

requirements progress- low forecast

accuracy

Y Items:- trends of rising

or falling requirements progress

- medium forecastaccuracy

X Items:- regular, non-fluctuating

requirements progress- high forecast accuracy

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� You can use the purchasing information system in purchasing. Using theABC analysis, you can classify vendors with regard to the Invoice amountkey figure.

� You can use the S&D information system in sales and distribution: Usingthe ABC analysis, you can classify sales organizations regarding the incom-ing orders key figure, and materials according to the Revenue key figure.

� In production, you can use the production information system. Using theABC analysis, you can classify work centers with regard to the Scrap quan-tity key figure.

� For your plant maintenance, you can use the plant maintenance informa-tion system. Using the ABC analysis, you can classify object classes withregard to the Breakdown duration key figure.

� To analyze your inventory you should use the inventory controlling modulein SAP: Using the ABC analysis, you can classify materials, materialgroups, storage locations, and even entire plants. For example, you canrun comparisons of material movements per storage location or of outgo-ing quantities at finished goods level per plant. By default, the SAP systemprovides a wide range of key figures for ABC and XYZ analyses, such asusage values, stock receipts values, safety stocks, average inventory levels, andthe number of material movements. Key figures like the usage or consump-tion can be measured in terms of quantities (e.g., kg, units, and so on) orvalue units (e.g., USD).

3.2.1 Outlining the Analysis Process

The following sections will outline an ABC analysis of the inventory control-ling component of mySAP ERP. Later in the chapter, we’ll do the same withan XYZ analysis. The ABC analysis is performed based on the following steps:

1. Determining the analysis goal

2. Defining the area to be analyzed

3. Calculating the data basis

4. Selecting the analysis basis as a subset of the data basis

5. Defining the ABC strategy and ABC class boundaries

6. Defining the priorities and assignment to the classes


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3.2.2 Determining the Analysis Goal

First, we need to define the questions that you want answered and deter-mine in which areas of the supply chain you expect the biggest potential foroptimization. In the following example, we’ll first conduct an ABC analysisfor the consumption quantity and then we’ll do a quantity flow analysis forthe individual storage locations in plant 1200.

In the mySAP ERP menu, select Logistics • Logistics Controlling • InventoryControlling • Standard Analyses • Plant.

3.2.3 Defining the Area to be Analyzed

Then select the objects to be analyzed (materials, customers, ...) and the cor-responding timeframe (year, month, …) that you want to use at the begin-ning of the analysis. You can extend the analysis at a later stage in iterativesteps.

Figure 3.5 illustrates the selection of an ABC plant analysis in the inventorycontrolling area of mySAP ERP.

Figure 3.5 Selecting the ABC Analysis in mySAP ERP

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In the upper section, you can see the Characteristics field group where youcan select the objects on which you want to run an ABC analysis. Enter 1200for the plant. You can also restrict the selection to specific storage locationsor exclude specific storage locations from the selection, for example, con-signment storage locations.

The Material Groupings field group enables you to further restrict the selec-tion, for example, according to material types (e.g., only finished products)or material groups.

The timeframe for the ABC analysis can be entered in the Period to Analyzefield. For seasonal items, you should enter at least one entire year. If youwant to analyze the material consumption only within the season, then youcan enter only the period of one season. The longer the period you select, themore significant the trend you identify. For products with a very short prod-uct lifecycle (e.g., mobile phones), you should select the product lifecycleperiod. It is extremely important that you choose the right data basis for theanalysis.

Moreover, you can use the Valuation field group to determine how theinventory is to be evaluated. Select the Standard entry if you want to refer tothe standard price that is stored in the material master.

The determination of the inventory value is essential for the ABC analysis,because the value is used as a basis for separating the materials into A, B, andC materials. For this purpose, you should determine a separate value for eachitem in the data basis, for example: annual requirements in units x cost priceper unit.

The next step is carried out automatically in mySAP ERP on the basis of theprices stored in the material master. Figure 3.6 shows that Material T-B1000is standard-price-controlled. Go to the material master and select Logistics •Production • Master Data • Material Master • Material • Change • Immedi-ately. Then go to the Costing 2 view (Price control = S). The current standardprice is set to 315 Euro and 98 cents.

Figure 3.7 shows the subsequent screen. It shows that Material T-B1000 isspecified with a goods receipt value of 31,598.00 Euro. This means that thereceived quantity of 100 PCs was valuated with the standard price of 315.98Euro from the material master.


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The only remaining parameter you can still define is the Analysis Currency.If you specify an analysis currency, all key figure values are converted intothe specified currency and therefore calculated in a standard format. Thespecification of an analysis currency can entail longer runtimes. For this rea-son, you should specify an analysis currency only if you’re sure that the sys-tem will output different currencies and you want the results to be displayedin only one currency. The currency translation is based on the currency type

Figure 3.6 Prices Are Automatically Taken from the Material Master in mySAP ERP

Figure 3.7 Key Figure Values are Calculated on the Basis of Quantities and Prices

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for the exchange rate that is valid on the system date. The currency type iseither stored in the user settings or can be specified in Customizing.

You can also specify a defined exception in the parameters using the earlywarning system. The exceptional situations defined in the Exception param-eter are then highlighted in color in the standard analyses. A prerequisite isthat the standard analysis and the exception are based on the same informa-tion structure and that the exception has been activated for the standardanalyses. The use of different colors enables you to easily navigate within thestandard analysis. For example, if exceptions occur at the materials level (forinstance with a material stock of more than 1m USD), they are displayed at ahigher aggregation level (for example at the plant level).

3.2.4 Calculating the Data Basis

Make sure your data basis is consistent. The data basis consists of all charac-teristics (for example, material numbers) and key figures, such as the con-sumption quantity and value that you have selected for the ABC analysis.Take your time when carrying out the first ABC analysis and pay attention toquality. The recurring efforts for staging the data basis should be kept at aminimum level so that you can perform the ABC analysis continuously.Another important factor is the cleansing of data. Many ERP systems oftencontain unused materials that are included in data selections, which actuallyshouldn't be the case. It also happens that materials are selected because theystill have a small stock value but have already been marked for deletion.

You should therefore pay particular attention to the following aspects whenselecting and cleansing your data:

� Scrap materials that show no goods movement

� Delete materials from the data basis that have been marked for deletion

� Complement your data with missing prices, units of measure, and so on

� Scrap materials with negative values

You should first examine your data basis and then decide on the key figuresthat you want to analyze in the ABC analysis. If you choose a wide data basis,you can narrow it down step by step and evaluate it according to specific val-ues. In our example, the plant analysis result first displays the value stockreceipts and value stock issues, as well as the total usage key figures thathave been previously set in the standard selection profile, as shown in Figure3.8.


67

Figure 3.9 shows the definition of key figures on which you want to baseyour ABC analysis in mySAP ERP. Once you have selected the data basisusing a set of key figures, you can follow the menu path Goto • Select key fig-ures to make your selection.

Figure 3.8 Basic List for an ABC Analysis with Key Figures: Value Stock Issues, Value Stock Receipts, and Total Usage

Figure 3.9 Selecting Key Figures for an ABC Analysis

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The system displays all available key figures of your data basis (Pool), as wellas the key figures you actually selected by using the arrow buttons (Selectioncriteria). For our ABC analysis, we'll select the key figures Valuated stockand Valuated Stock Value.

Next, we’ll obtain the analysis based on the selected key figures. Then youcan classify the data at the key figures level to examine the data basis prior tothe actual ABC classification and to define the ABC boundaries (see Figure3.10). To do that, you should highlight the key figure you want to classifyand then click on the Sort button.

3.2.5 Defining the ABC Strategy

Once you have defined the data basis and the key figures for the ABC analy-sis, you must select a strategy. To do that, you must once again select a keyfigure and then click on Edit • ABC Analysis. The system displays the screenin which you can select the ABC strategy, as shown in Figure 3.11.

Figure 3.10 The Dataset Can Be Sorted According to Selected Key Figures


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After selecting the strategy, you must select the ABC strategy parameters:

In Figures 3.11 and 3.12, you can see the analysis strategy and the classboundaries we defined in mySAP ERP for our example. We decided to usethe standard strategy, Total ValStockValue (%) and the standard class bound-aries: A = 70%, B = 20%, and C = 10%.

Prior to the actual analysis in the ABC analysis, you must define the analysisstrategy, as described above. To do that, mySAP ERP provides the followingfour strategies:

Total Key Figure (%)

The total of the characteristic values (materials) assigned to the A, B, or C seg-ment represents a specific percentage of the total value of the key figure (inthe above example, that's the total valuated stock value).

An example: You enter 70% for the A segment, 20% for the B segment, and10% for the C segment. These values have proven useful in actual practice;however, you can also use slightly modified values if you have already runthe ABC analysis on the same data basis several times and concluded that themodified settings are more appropriate for your data basis.

Figure 3.11 Selecting the ABC Strategy

Figure 3.12 Selecting the ABC Strategy Parameters

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The system creates an internal list that is sorted by the key figure values indescending order. The A segment is assigned all values that represent 70% ofthe total key figure value. The B segment is assigned the values representing20%, and the C segment is assigned the values that represent 10% of the totalkey figure value.

Number of Characteristic Values (%)

The number of characteristic values (the number of materials in the aboveexample) that are assigned to the A, B, and C segments is provided as a per-centage of the total number.

An example: You enter 10% for the A segment, 30% for the B segment, and60% for the C segment. The system creates an internal list that is sorted bythe key figure values in descending order. The A segment is assigned 10% ofthe total number of characteristic values with the highest key figure value,the B segment is assigned the following 30%, while the C segment isassigned 60% of the characteristic values with the lowest key figure value.

Key Figure (absolute)

The boundaries between the A and B and between the B and C segmentsmust be defined.

An example: You enter the value 500,000 to mark the boundary between theA and B segments, while 150,000 represents the boundary between the Band C segments. The A segment is then assigned all characteristic valueswhose key figure value is higher than 500,000. All characteristic valueswhose key figure value is between 150,000 and 500,000 are assigned to theB segment. And finally, all characteristic values whose key figure value islower than 150,000 are assigned to the C segment.

You should opt for this strategy only if you know your data basis very welland if you have previously performed several ABC analyses for the same databasis. This strategy helps you tune up your ABC analysis and performdetailed analyses.

Number of Characteristic Values

The number of characteristic values must be defined for the A and B seg-ments. All other characteristic values are assigned to the C segment.


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An example: You enter 20 as the value for the A segment, and 30 for the Bsegment. As a result of the ABC analysis, the system creates an internal listthat is sorted by the key figure values in descending order. The first 20 char-acteristic values in the list are assigned to the A segment, the next 30 valuesare assigned to the B segment, and the remaining values are assigned to theC segment.

You should choose this strategy only if you know your data basis very welland if you have previously performed several ABC analyses for the same databasis. This strategy can also be used for fine-tuning your ABC analysis. It isparticularly useful when you want to quickly identify the top 20 characteris-tic values and when you want to accelerate the ABC analysis when dealingwith large data quantities.

3.2.6 Defining Class Limits

After selecting the strategy, you must define the class limits. Note that theSAP system provides only one suggestion. You can define the final class lim-its in accordance with your requirements, and even define more than threeof them; however, the three limits have proven useful in actual practice.

Alternatively, Figure 3.13 shows the definition of six individual classes.

Figure 3.13 ABC Analysis with Six Individual Class Limits

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Six class limits are useful only if you want to perform a very detailed ABCanalysis and to further subdivide the standard A, B, and C classes. A real-lifeexample would be the more detailed separation of C materials. A large quan-tity of C materials, for example, can be subdivided into C1 materials (lowvalue) and C2 materials (very low value).

But let us now return to the ABC analysis with the three standard class limits.

3.2.7 Assigning Classes

The SAP system defines the ranking of the values (for example, rank No. 1 isthe highest annual requirement in USD) and sorts the materials in the subse-quent ABC analysis correspondingly. Here, it is useful to calculate aggregatedvalues with regard to the assignments to ABC limits. The system calculatesthe rank or the material as a percentage of the total value. Then, it calculatesthe aggregated percentage of the total value.

The respective materials are automatically assigned by the system to the pre-viously defined classes. The result you obtain is an ABC classification. Theidentified classification criterion for each material (A, B, or C) can be auto-matically stored in the material master data. If you don't use this function,you must manually enter the newly determined ABC identifiers in the mate-rial master.

Figure 3.14 displays the result of an ABC analysis in mySAP ERP, which youcan select via the following path: Edit • Segmentation.

The figure shows the class limits with their absolute values, the percentages,and aggregated values. In the above example, 0.85% (26 materials) repre-sents 70.40% of the total valuated stock value. By double-clicking on the

Figure 3.14 Overview of an ABC Analysis Result


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respective class, you can prompt the system to display the individual materi-als, including their values in greater detail (see Figure 3.15).

3.2.8 Evaluating an ABC Analysis

You can display the ABC analysis results as a totals curve or as a three-dimen-sional graphic.

Totals Curve

The totals curve can be displayed for absolute values or percentages. It pro-vides information on the relative concentration of materials. The abscissarepresents the number of materials (or the percentage of the number ofmaterials respectively), while the ordinate displays the aggregated consump-tion values or requirements values (or percentages of those values respec-tively).

Figure 3.15 Detailed View of an ABC Analysis Result

477

Index

3D graphic 74

A

A materials 57ABC analysis 53, 77, 270

evaluating 73with SAP 61

ABC segmentation 74ABC-XYZ matrix 54, 87Ability to deliver 264Absolute percent error 188, 189, 191Access fluctuations 60Accumulate balances 209Acquisition costs 31Actual range of coverage 340Additional lot-sizing procedures 342Adjusted absolute percent error 189,

193Adjusted R square 189, 197Aggregation 128, 174Aggregation level 174, 202Alert functions 186Alert Monitor 57, 204, 385, 419Alerts for container resources 405Alpha factor 171Analysis area 63Analysis goal 63Analysis of dead stock 453Analysis of slow-moving items 451Andler lot size 350Andler method 351APE 188, 191APS 371, 372ARIMA 162Assemble-to-order 255Assembly level 210, 254ATP 273, 274ATP explanation and simulation 276Automatic model selection 142Automatic planning 380, 399Availability check 281

organizational levels 278product levels 277several plants 279

Available-to-promise (ATP) 272Average consumption key figure 454Average inventory level key figure 454

B

B materials 57Backflush 232Backlog resolution 402Backlogs 369, 370, 373Backlogs in production 365Backorder 267Baseline forecast 111Basic ATP methods 274Bass model 151Beta factor 172Block cycles 407Block planning 406Bottleneck 365Box-Jenkins method 139, 162Buffer stocks 28, 42, 366Bullwhip effect 96

C

C materials 58Campaign planning 391Cannibalization 102, 122Capable-to-promise 425Capacity tie-up 34Capital tie-up 34Causal forecast errors 197Causal models 135, 164Characteristic level 255CIF 430Class limits 71Coefficient of determination 197Compact planning 410Competitors 100Component level 254Component stocks 30Composite forecast 172Composite forecast methods 150Composite methods 136Confirmation discipline 108

478

Index

Constant model 134, 153Constant progression 134Constant requirements 350Constraint propagation 414Consumption cycle 460Consumption parameters 211Consumption variance 37Container resource 403Continuous in-/output 342Controlling the production selection 278Core Interface 430Corrected forecast 111Corrected history 110Cost function 359Cost optimization 349Cost portions 21Cost reduction strategies 369Cost-balancing method 352Costs for production coordination 34Costs generated by a capacity tie-up 34Costs generated by process errors 34Coverage time 288Cross-plant network planning (SNP) 427Cross-system processes 43Croston method 145, 161Customer-specific heuristics 411Cyclical component 115

D

Daily lot size 334Data basis

calculating 66correcting 109creating 106

Data collection 445Data quality 107Days' supply 340Dead stock key figure 452Decrease in flexibility 34Delay costs 413Delivery 207Delivery cycle 335Delivery date variances 37Delivery flexibility 49, 265Delivery quality 266Delivery quantity variances 38Delivery reliability 263, 264Delivery time 117, 264

Delta factor 172Demand determination 208Demand planning 46, 93Demand uncertainty 36Demand-driven MRP 253Depreciation 22Deseasonalization 159Detailed scheduling heuristics 387, 402Deterministic demand determination

208Deterministic lot-sizing procedures 327,

346Disaggregation 128Disposal 22Distant market 99Distribution resource planning 41DS Planning Board 434Durbin-h 189, 198Durbin-Watson 189, 198Dynamic lot-size calculation 357Dynamic pegging 383Dynamic safety stock 291, 296, 309

E

Early warning system 66Economic lot-sizing procedures 347Error measure 182Error total 188, 189Events 112, 121, 137, 174Exact lot size 328Exception 66Exponential smooting 153Ex-post forecast 114, 186External optimizers 418

F

Feasible production plan 375Fierce competition 98Find slot 376, 408Finished goods stock 29Finished product level 254Finite planning 379Finite production plan 374Finite scheduling 370Fixed lot size 329, 330Fixed pegging 383Fixed ranges 336

479

Index

Flowchart 458Fluctuation coefficient 60Forecast 93, 97Forecast accuracy 45, 94, 130, 186, 203,

257Forecast alerts 205Forecast analysis 180Forecast comparison 184Forecast error 40, 99, 182, 185, 188,

286, 317Forecast frequency 173Forecast horizon 116, 117, 173, 181Forecast level 128Forecast method 132, 139, 148Forecast parameters 182Forecast period 173, 174Forecast quality 283, 302, 314Forecast responsibility 127Forecast settings 183Forecast-based demand determination

208Forecast-based MRP 253Forecasting 46Forecasting process 128Forward buying 118Fulfillment rate 438

G

Gamma factor 172Genetic algorithm 414Geometric mean relative absolute error

(GMRAE) 189, 195Global ATP 272Goodness of fit 197Graphical DS planning board 424Graphical Planning Board 386Groff lot-sizing procedure 356Groff procedure 359Gross requirements 209Gross requirements planning 220Growth stage 101

H

Harris method 350Heuristics 387Historical consumption 106Historical period 174

Holt procedure 157Hourly lot size 342

I

Idle time 367Imitators 151Import tariff 99Infinite planning 408Information system 440Innovators 151Insert operation 408Insurance 22Interactive optimization 414Introduction stage 101Inventory analysis 53, 458Inventory concepts 28Inventory controlling 62, 75, 437, 462Inventory cost elements 21Inventory key figures 446Inventory level at receipt key figure 457Inventory maintenance 34Inventory management 22, 43Inventory monitoring 52, 462Inventory policy 317Inventory strategies 207Inventory turnover 46, 287Inventory turnover key figure 449Inventory value key figure 452Inventory variances 39Inventory-taking 59

K

Key figures 439

L

Lead time 42, 116, 325, 367, 368Lead time reduction 402Least unit cost procedure 354Lifecycle 106Lifecycle forecast 167Lifecycle planning 102, 184Like modeling 103Linear regression 145LMN analysis 458Local market 99Logistics controlling 437, 438, 462

480

Index

Lorenz curve 55Lot size 50, 207, 216, 325Lot-for-lot procedure 328Lot-size creation 42Lot-size key figure 457Lot-size-independent production costs

348

M

Macro alert 206MAD 188, 190Make to order 29Make-to-order (MTO) 234, 255, 265Make-to-order production 237Make-to-stock (MTS) 255, 265Make-to-stock production 209

anonymous 249customer-independent 209strategies 211

Manual forecast 148Manufacturing costs 325MAPE 188, 193Market dynamics 98Market influences 98Marketplace 99Master data parameters 252Material and capacity requirements plan-

ning 380Material costs 348Material groupings 64Material range of coverage 447Material requirements planning 47, 207,

335consumption-based 239forecast-based 239, 242optimization 251time-phased 246time-phased materials planning 239,

242with delivery cycle 246with reorder point planning 248

Material requirements solution 207Maximum clearances 410MdAPE 194MdRAE 195Mean absolute deviation (MAD) 188,

190Mean elasticity 189, 199

Mean percent error (MPE) 188Mean square error (MSE) 188, 190Median 115, 189, 195Median absolute percent error (MdAPE)

189Median method 163Median relative absolute error (MdRAE)

189Messages 183MLR 197Mode costs 413Model selection

automatic 140manual 138

Monthly lot size 335Moving average model 149MPE 188MRP cycles 42MRP heuristics 375, 398MRP levels 398MRP procedure 239MRP strategy 208, 210, 212, 251, 254MRP-II concept 370, 372MSE 188, 190MTO production 267Multi output planning 394Multilinear regression 164Multi-resource planning 389

N

Naive methods 136Net requirements 209

calculation 207planning 218

Non-working times 411Normal distribution 283, 284, 301

with variances 285

O

Objective function of optimization 415Objectives 43Optimal lot-sizing procedures 347, 359Optimization algorithms 414Optimization Extension Workbench 418Optimization methods 412Optimization potentials

demand side 40

481

Index

deriving 87forecast 97in safety stocks 301master data 270order processing 266planning 268production 269service level 266supply side 41

Optimizer 414Order calculation 209Order cycle policy 317Order cycles 60Order processing 270, 271Order transfer 215Ordering costs 30, 348Outlier 138Outlier correction 114, 145, 183Overplanning 228

P

Parameter optimization 171Part-period balancing 352, 359Part-period method 352Pegging 382, 384Period adjustment 175Period lot sizes 335Period profile 298Period to analyze 64Periodic lot-sizing procedures 333Phase-in/phase-out 102, 104, 184Planned independent requirements 209,

215Planning

at assembly level 229at component level 229at phantom assembly level 231with final assembly 213, 249with planning material 212, 226without final assembly 212, 222, 249without final assembly for make-to-order

production 235Planning at assembly level 211Planning calendar 335Planning components 229Planning cycle 335Planning levels 254, 427Planning mode 376

Planning product 249Planning sequence 410Planning strategies 211, 229, 234Planning tools 431Planning with item backlog 366Planning without backlogs 379Plant maintenance 22, 76Points in time 202Pool 68Portfolio matrix 80Posting periods 335PPS planning calendar 335Practitioner rules 333Price variances 38Primary demand 208Process error 34Process key figures 443Process uncertainty 36Procurement cycle 460Procurement lead times 41Procurement market research 59Procurement quantities 41Procurement strategies 256Product heuristics 388Product influences 100Product lifecycle 100, 137, 167Product planning board 431Product segmentation matrix 139Product substitution 279Product variants 42, 279Production 50, 75, 365Production coordination 34Production output 42Production plan 212, 373Production planning heuristics 387Production program 208Production type 209Promotion data basis 123Promotion planning 119, 121, 124Promotions 112, 118, 121, 137, 174Purchasing 75Push production 393

Q

Qualitative forecast methods 132Quantitative forecast methods 133Quantity flow analysis 79

482

Index

R

R square 167, 189, 197RAE 195Random component 116Range of coverage 288, 294

key figure 446, 454profile 244, 245, 337

Rate of inflation 98Raw material stocks 30Readiness to deliver 260, 261, 262, 263Receipt days' supply 340Receipt value of valuated inventory key

figure 455Regression analysis 142Relative absolute error 189, 195Release modalities 207Reorder level 240, 254, 287Reorder point 289Reorder point planning 240, 331Reorder point policy 317Repetitive manufacturing 389, 431Replenishment lead time 33, 240, 252,

253, 257, 258, 280, 283, 313Replenishment up to maximum stock

level 330Requirement fluctuations 212Requirements forecast 270Requirements planning 59Requirements strategies in SAP APO 248Resolving backlogs 377Rest component 116Return on investment 22RMSE 188, 191ROI costs 34Rule-based check 276Running a forecast 170, 175

S

Safety days' supply 306Safety range of coverage 305Safety stock 30, 244, 252, 257, 284, 289Safety stock buffer key figure 455Safety stock key figure 456Safety stock planning 302, 312, 323Safety time 296, 340

profile 298Sales and distribution 75

Sales forecasts 210Sales goals 130Sales orders 212Sales-order-related production 209Saturation stage 101SCOR 438, 441, 443SCOR Model Level 1 441SCOR Model Level 2 442SCOR Model Level 3 442Seasonal component 116Seasonal linear regression 145, 159Seasonal model 134Seasonal trend pattern 134Seasonalization 160Season-like pattern 134Secondary demand 208Selection model 138Selection of lot-sizing procedures 363Semifinished goods stock 29Service heuristics 400Service level 48, 254, 259, 266, 284,

286, 313, 317influencing factors 270

Setup changes 42Setup costs 412Setup optimization 416Setup times 412Shift lot size 342Shorage quantities 389Silver meal method 356Slow-moving items key figure 450SMI 42SNP 427Sporadic pattern 135Squeeze in operation 409Stable forward scheduling 407Standard lots 388Static safety stock 301Statistical range of coverage calculation

337Stochastic lot-sizing procedures 327Stock build-up 28Stockholding costs 21, 349Stocking level 210, 251Stockout calculation 314Stockout costs 22, 31, 349Stocks 19Storage cost rate 354Storage costs 257

483

Index

Storage range 89Streamlining the range of goods 40Subassembly planning 211Supply chain 27

uncertainties 36Supply Chain Council 440Supply network planning 304

T

Taxes 22Theil coefficient 196Time buffer 296Time series 115Time series analysis 134Time-phased materials planning 244Total lead time 412, 460Total usage 66Total valuated stock value 69Totals curve 73Tracking signal 196Transparency 43Transparency of costs 302Transport times 41, 367Trend component 115Trend model 134Trend models and seasonal models 156Trend-like pattern 134t-Test 189, 199Two-points function 152

U

Underplanning 228Univariate forecast errors 189Univariate forecast models 134

V

Valuated Stock 68Valuated Stock Value 68Value analysis 59Value assessment 467Value stock issues 66Value stock receits 66Variant products 227Variation coefficient 84Vendor performance 41Version management 420Volume discounts 30

W

Wagner & Whitin 357Warehouse optimization 77Weekly lot size 334Weighted moving average model 149Winters procedure 157Work days 113

X

X materials 60XYZ analysis 53, 60, 81, 139

with SAP 81

Y

Y materials 60

Z

Z materials 60

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Inventory Optimization with SAP - cdn.ttgtmedia.com · Contents at a Glance Introduction..... 19 1 Why Inventory Is Necessary..... 27